Update README.md

README.md

@@ -18,7 +18,56 @@ AlphaFold2通过从蛋白质序列和结构数据中提取信息，使用神经
 
 ![img](./docs/alphafold2_1.png)
 
+
 ## 环境配置
+
+### Docker
+    
+    docker pull image.sourcefind.cn:5000/dcu/admin/base/jax:0.4.23-ubuntu20.04-dtk24.04.1-py3.10
+
+    docker run --shm-size 50g --network=host --name=alphafold2 --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v 项目地址(绝对路径):/home/ -v /opt/hyhal:/opt/hyhal:ro -it <your IMAGE ID> bash
+
+    # 1. 一般依赖项安装
+    pip install -r requirements_dcu.txt
+
+    pip install dm-haiku==0.0.11 flax==0.7.1 jmp==0.0.2 tabulate==0.8.9 --no-deps jax
+
+    pip install orbax==0.1.6 orbax-checkpoint==0.1.6 optax==0.2.2
+
+    python setup.py install
+
+    # 2、hh-suite 
+
+    git clone https://github.com/soedinglab/hh-suite.git
+    mkdir -p hh-suite/build && cd hh-suite/build
+    cmake -DCMAKE_INSTALL_PREFIX=. ..
+    make -j 4 && make install
+    export PATH="$(pwd)/bin:$(pwd)/scripts:$PATH"
+
+    wget https://github.com/TimoLassmann/kalign/archive/refs/tags/v3.4.0.zip
+    unzip 3.4.0.zip && cd kalign-3.4.0
+    mkdir build 
+    cd build
+    cmake .. 
+    make 
+    make test 
+    make install
+
+    # 3. openmm + pdbfixer
+
+    sudo apt install doxygen
+
+    wget https://github.com/openmm/openmm/archive/refs/tags/8.0.0.zip
+
+    unzip 8.0.0.zip && cd openmm-8.0.0 && mkdir build && cd build
+
+    cmake .. && make && sudo make install && sudo make PythonInstall
+
+    wget https://github.com/openmm/pdbfixer/archive/refs/tags/1.9.zip
+
+    unzip 1.9.zip && cd pdbfixer-1.9 && python setup.py install 
+
+<!-- ## 环境配置
 提供[光源](https://www.sourcefind.cn/#/image/dcu/custom)拉取推理的docker镜像：
 ```
 docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:alphafold2-2.3.2-dtk23.10-py38
@@ -32,7 +81,7 @@ docker run -it --name alphafold --privileged --shm-size=32G  --device=/dev/kfd -
 * DTK驱动：dtk23.10
 * Jax: 0.3.25
 * TensorFlow2: 2.11.0
-* python: python3.8
+* python: python3.8 -->
 
 ## 数据集
 推荐使用AlphaFold2中的开源数据集，包括BFD、MGnify、PDB70、Uniclust、Uniref90等,数据集大小约2.62TB。数据集格式如下：